An Ironing-Based Approach to Adaptive Online Mechanism Design in Single-Valued Domains
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CitationParkes, David C. and Quang Duong. 2007. An ironing-based approach to adaptive online mechanism design in single-valued domains. In Proceedings of the Twenty-second AAAI Conference on Artificial Intelligence: July 22-26, 2007, Vancouver, British Columbia, Canada, ed. American Association for Artificial Intelligence, 94-101. Menlo Park, Calif.: AAAI Press.
AbstractOnline mechanism design considers the problem of sequential decision making in a multi-agent system with self-interested agents. The agent population is dynamic and each agent has private information about its value for a sequence of decisions. We introduce a method ("ironing") to transform an algorithm for online stochastic optimization into one that is incentive-compatible. Ironing achieves this by canceling decisions that violate a form of monotonicity. The approach is applied to the CONSENSUS algorithm and experimental results in a resource allocation domain show that not many decisions need to be canceled and that the overhead of ironing is manageable.
Citable link to this pagehttp://nrs.harvard.edu/urn-3:HUL.InstRepos:4039777
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